An enormous amount of information has accumulated about the molecular components that govern the cell division cycle and apoptosis; information that is crucial to the development of new anti-cancer therapies. However, the relevant molecular interaction networks are so complicated that it is often difficult to understand exactly how they function. Diagramming these networks presents a major challenge, because of the large role played by multimolecular complexes and modification contingencies . Yet comprehensive diagrams, using a standardized notation, are essential in the same way that circuit diagrams are essential in electronics. Several years ago, we devised a notation for molecular interaction maps (MIM) that many in the field now consider to be the best way to represent the networks in detail. We have used MIMs in many publications and examples have been prominently displayed in journal issues (such as being featured on the cover). MIMs however have not yet been widely used by others, presumably because of the effort required to learn the rules of the notation. Our colleagues have found the effort to be well worth while, in part because adhering to the rules of the MIM notation imposes a discipline of logic that enforces clear understanding. In order to help others adopt the notation, we published an article this year that more clearly defines the rules of the notation and that provides a systematic set of examples (Kohn et al. (2006) Mol. Biol. Cell 17: 1-13). The article can serve both as a reference manual and as a tutorial. By publishing this article in a major cell biology journal, we aimed for the broad cell biology community, rather than narrowly for bioinformaticists and systems biologists. The editors selected examples of our molecular interaction maps for display on the journal cover in order to bring our method to the attention of a wide audience of cell biologists.Relevant to bioinformatics and systems biology, we prepared another article (Kohn et al. (2006) Mol. Syst. Biol., in press), in which we address two major issues. First, we show the advantages of the MIM notation relative to other proposed notations. Second, we show how the MIM notation can represent networks for combinatorial simulation, a capability not shared by any other proposed notation. To demonstrate this point, we prepared a concise representation of a combinatorial simulation of the core of epidermal growth factor signaling recently published by Blinov et al, consisting of over 3000 individual reactions. This insight then led to a collaboration with Michael Blinov et al, in which we plan to mesh our MIM notation with their combinatorial network program. On the computation front this year, our group began a simulation study of the role of Mdmx in the response of p53 to DNA damage. In collaboration with Dr. Mirit Aladjem in our Laboratory, we plan to link simulation results with experiments.